cov.trob {MASS}  R Documentation 
Estimates a covariance or correlation matrix assuming the data came from a multivariate t distribution: this provides some degree of robustness to outlier without giving a high breakdown point.
cov.trob(x, wt = rep(1, n), cor = FALSE, center = TRUE, nu = 5, maxit = 25, tol = 0.01)
x 
data matrix. Missing values (NAs) are not allowed. 
wt 
A vector of weights for each case: these are treated as if the case i
actually occurred wt[i] times.

cor 
Flag to choose between returning the correlation (cor = TRUE ) or
covariance (cor = FALSE ) matrix.

center 
a logical value or a numeric vector providing the location about which
the covariance is to be taken. If center = FALSE , no centering
is done; if center = TRUE the MLE of the location vector is used.

nu 
“degrees of freedom” for the multivariate t distribution. Must exceed 2 (so that the covariance matrix is finite). 
maxit 
Maximum number of iterations in fitting. 
tol 
Convergence tolerance for fitting. 
A list with the following components
cov 
the fitted covariance matrix. 
center 
the estimated or specified location vector. 
wt 
the specified weights: only returned if the wt argument was given.

n.obs 
the number of cases used in the fitting. 
cor 
the fitted correlation matrix: only returned if cor = TRUE .

call 
The matched call. 
iter 
The number of iterations used. 
J. T. Kent, D. E. Tyler and Y. Vardi (1994) A curious likelihood identity for the multivariate tdistribution. Communications in Statistics—Simulation and Computation 23, 441–453.
Venables, W. N. and Ripley, B. D. (1999) Modern Applied Statistics with SPLUS. Third Edition. Springer.
data(stackloss) cov.trob(stackloss)